Proceedings of the Fifth SIAM International Conference on Data Mining

Proceedings of the Fifth SIAM International Conference on Data Mining

Author: Hillol Kargupta

Publisher: SIAM

Published: 2005-04-01

Total Pages: 670

ISBN-13: 9780898715934

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The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.


Proceedings of the Eighth Workshop on Algorithm Engineering and Experiments and the Third Workshop on Analytic Algorithmics and Combinatorics

Proceedings of the Eighth Workshop on Algorithm Engineering and Experiments and the Third Workshop on Analytic Algorithmics and Combinatorics

Author: Rajeev Raman

Publisher: SIAM

Published: 2006-01-01

Total Pages: 298

ISBN-13: 9780898716108

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The annual Workshop on Algorithm Engineering and Experiments (ALENEX) provides a forum for the presentation of original research in all aspects of algorithm engineering, including the implementation and experimental evaluation of algorithms and data structures. The workshop was sponsored by SIAM, the Society for Industrial and Applied Mathematics, and SIGACT, the ACM Special Interest Group on Algorithms and Computation Theory. The aim of ANALCO is to provide a forum for the presentation of original research in the analysis of algorithms and associated combinatorial structures.


Proceedings of the Fourth SIAM International Conference on Data Mining

Proceedings of the Fourth SIAM International Conference on Data Mining

Author: Michael W. Berry

Publisher: SIAM

Published: 2004-01-01

Total Pages: 556

ISBN-13: 9780898715682

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The Fourth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. This is reflected in the talks by the four keynote speakers who discuss data usability issues in systems for data mining in science and engineering, issues raised by new technologies that generate biological data, ways to find complex structured patterns in linked data, and advances in Bayesian inference techniques. This proceedings includes 61 research papers.


Proceedings of the Sixth Workshop on Algorithm Engineering and Experiments and the First Workshop on Analytic Algorithmics and Combinatorics

Proceedings of the Sixth Workshop on Algorithm Engineering and Experiments and the First Workshop on Analytic Algorithmics and Combinatorics

Author: ACM Special Interest Group for Algorithms and Computation Theory

Publisher: Siam Proceedings in Applied Ma

Published: 2004

Total Pages: 250

ISBN-13:

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The aim of the annual ALENEX workshop is to provide a forum for the presentation of original research in the implementation and experimental evaluation of algorithms and data structures. This research presents significant studies in experimental analysis or in the implementation, testing, and evaluation of algorithms for realistic environments and scenarios. The paper presentations address specific applied areas that present unique challenges in their underlying algorithmic problems as well as methodological issues and standards in the context of empirical research on algorithms and data structures. analysis of algorithms and associated combinatorial structures. The papers study properties of fundamental combinatorial structures that arise in practical computational applications (such as permutations, trees, strings, tries, and graphs) and address the precise analysis of algorithms for processing such structures, including average-case analysis; analysis of moments, extrema, and distributions; and probabilistic analysis of randomized algorithms. This proceedings collects extended versions of the 14 papers that were selected for presentation from the ALENEX workshop and 10 papers selected for presentation from the ANALCO workshop.


Proceedings of the Sixth SIAM International Conference on Data Mining

Proceedings of the Sixth SIAM International Conference on Data Mining

Author: Joydeep Ghosh

Publisher: SIAM

Published: 2006-04-01

Total Pages: 662

ISBN-13: 9780898716115

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The Sixth SIAM International Conference on Data Mining continues the tradition of presenting approaches, tools, and systems for data mining in fields such as science, engineering, industrial processes, healthcare, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, based on sound statistical foundations. These techniques in turn require powerful visualization technologies; implementations that must be carefully tuned for performance; software systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them.


Mathematics for Industry

Mathematics for Industry

Author: David R. Ferguson

Publisher: SIAM

Published: 2005-01-01

Total Pages: 260

ISBN-13: 9780898715989

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The papers were elicited primarily from Mathematics for Industry: Challenges and Frontiers, a conference sponsored by SIAM in October, 2003.


Proceedings of the Seventh SIAM International Conference on Data Mining

Proceedings of the Seventh SIAM International Conference on Data Mining

Author: Chid Apte

Publisher: Proceedings in Applied Mathema

Published: 2007

Total Pages: 674

ISBN-13:

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The Seventh SIAM International Conference on Data Mining (SDM 2007) continues a series of conferences whose focus is the theory and application of data mining to complex datasets in science, engineering, biomedicine, and the social sciences. These datasets challenge our abilities to analyze them because they are large and often noisy. Sophisticated, highperformance, and principled analysis techniques and algorithms, based on sound statistical foundations, are required. Visualization is often critically important; tuning for performance is a significant challenge; and the appropriate levels of abstraction to allow end-users to exploit sophisticated techniques and understand clearly both the constraints and interpretation of results are still something of an open question.